Video clip selector for medical imaging and diagnosis

ABSTRACT

A method for clip selection includes receiving through an interface to a medical imaging device, a selection of a diagnostic procedure and a target portion of a mammalian body. Thereafter, the device acquires video clip imagery of the target portion and stores the video clip imagery in an image store. Each video clip of the video clip imagery is then image processed to determine a view and a quality of each video clip and a rule is retrieved from a rules base corresponding to the selected diagnostic procedure and target portion. In this regard, the rule specifies a requisite view and quality of the video clip imagery. Finally, the retrieved rule is applied to the video clip imagery as a filter to produce a subset of video clip imagery satisfying the specified requisite view and quality and the subset of video clip imagery is stored in the image store.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.16/839,040, filed Apr. 2, 2020, which is a Continuation of U.S. patentapplication Ser. No. 16/016,725, filed Jun. 25, 2018, the entirety ofeach which is incorporated herein by reference.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates to the field of medical imaging anddiagnosis and more particularly to video clip selection for use inmedical imaging and diagnosis.

Description of the Related Art

Medical imaging refers to the process of creating a visualrepresentation of an interior portion of a mammalian body for thepurpose of clinical analysis and medical intervention. Medical imagingseeks to reveal internal structures hidden by the exterior of the bodyso as to facilitate the diagnosis and treatment of disease. Medicalimaging incorporates several different modalities for image acquisition.Common modalities include radiological devices such as X-ray radiographyincluding computerized tomography (CT), magnetic resonance imaging(MRI), medical ultrasonography or ultrasound, endoscopy, elastography,tactile imaging, thermography, medical photography and nuclear medicinefunctional imaging techniques as positron emission tomography (PET) andSingle-photon emission computed tomography (SPECT). Depending upon thedesired use of the imagery for the purpose of a medical diagnosis or thetargeting of specific tissue or a particular organ or portion of anorgan, different modalities for different imagery may be preferred.

Medical imaging of a target area of the body may be achieved from manydifferent views. Strictly speaking, in so far as medical imagery may betwo-dimensional in nature, the angle and approach of the imaging devicewill result in a different perspective view of the target area. As inthe case of the modality of medical imaging, a particular view of thetarget area presented in a medical image may be preferred depending uponthe desired use of the imagery for the purpose of a medical diagnosis orthe targeting of specific tissue or a particular organ or portionthereof.

Finally, medical imaging of a target area of the body may vary inquality. That is to say, depending upon the operator—usually atechnician and not the physician ultimately producing a diagnosis basedupon the imagery—the clarity and focal point of a medical image mayvary. In some instances, an attempted view of a target organ may beincomplete omitting key features of the target organ from the view dueto an improper placement of the imaging sensor. In other instances,external factors such as the anatomical features of the body may inhibitclarity of key features of the target organ despite proper placement ofthe imaging sensor.

The traditional workflow for medical imaging begins with the use of theimaging modality by a technician upon the patient in order to acquire aset of imagery. The imagery may be still imagery or video clip imagerydepending upon the modality. Generally, the technician enjoys anawareness of the ultimate purpose of the imagery so as to diagnose aparticular disease or dysfunction of a target organ. Once acquired, theset of imagery is stored in a centralized repository, typically referredto as a “PACS” or “Picture Archival Communications System” and a report,either digital or written, is prepared for review by the physician. Thephysician then retrieves at a later time the set of imagery and thereport and conducts an analysis of the imagery. The analysis generallyrequires the physician to select the most appropriate images in the setof imagery of the correct views and quality.

This process can be quite tedious—especially given the need for thephysician not only to select the correct images of the correct views andquality, but also to efficiently arrange on the display screen thecorrect images so as to facilitate a diagnosis through the concurrentreview of multiple different images of interest. To the extent that therequisite quality of an image does not exist in the set of imagery, butis required, or to the extent that the requisite view of an image doesnot exist in the set of imagery, the physician must then direct thepatient to return for an additional appointment for the technician tore-acquire the missing imagery. So much reflects an enormous waste ofresources of the patient, health care facility and physician.

BRIEF SUMMARY OF THE INVENTION

Aspects of embodiments of the invention summarized herein address theforegoing deficiencies and provide a novel and non-obvious method, dataprocessing system and computer program product for clip selection formedical imaging. A method of the invention includes receiving through aninterface to a medical imaging device, a selection of a diagnosticprocedure and a target portion of a mammalian body. Thereafter, themedical imaging device acquires a multiplicity of video clip imagery ofthe target portion and stores the video clip imagery in an image store.Each video clip of the video clip imagery is then image processed todetermine a view and a quality of each video clip and a rule isretrieved from a rules base corresponding to the selected diagnosticprocedure and target portion. In this regard, the rule specifies arequisite view and quality of the video clip imagery so as to achieve aparticular measurement necessary in performing the diagnostic procedure.Finally, the retrieved rule is applied to the video clip imagery as afilter to produce a subset of video clip imagery satisfying thespecified requisite view and quality and the subset of video clipimagery is stored in the image store.

In one aspect of the embodiment, on the condition that a video clipsatisfying the specified requisite view and quality in the video clipimagery is determined upon the application of the retrieved rule not toexist in the video clip imagery, an alert is generated through theinterface of the medical imaging device. In another aspect of theembodiment, the image processing of each video clip includes submittingeach video clip to a neural network trained to generate outputindicating a recognized view in a submitted video clip at a specifiedlevel of confidence, or in the alternative, submitting each video clipto a content based image retrieval system adapted to compare a submittedvideo clip to a data store of known images of particular views so as toindicate a recognized view in the submitted video clip.

In yet another aspect of the embodiment, the image processing of eachvideo clip further includes computationally computing a generalizeddegree of quality of a submitted image based upon the specified level ofconfidence produced in the output of the neural network. Finally, ineven yet another aspect of the embodiment, the rule additionallyspecifies a requisite presence of a landmark feature in the view. Inthis way, the image processing of each video clip includes submittingeach video clip to a neural network trained to generate outputindicating a recognized landmark feature in a submitted video clip at aspecified level of confidence, such that during application of theretrieved rule, an absence of the landmark feature correlates to poorquality of the video clip, but a presence of the landmark featurecorrelates to good quality of the video clip.

In another embodiment of the invention, a medical imaging dataprocessing system is configured for clip selection. The system includesa host computing system that includes one or more computers, each withmemory and at least one processor. A diagnostic imaging computer programexecutes in the memory of the host computing system and provides controlinstructions to a communicatively coupled medical imaging device. Theprogram additionally provides an interface to the medical imagingdevice.

Importantly, the program yet further includes computer programinstructions enabled during execution to perform a method of clipselection for medical imaging. The method includes receiving through aninterface to a medical imaging device, a selection of a diagnosticprocedure and a target portion of a mammalian body. Thereafter, themedical imaging device acquires a multiplicity of video clip imagery ofthe target portion and stores the video clip imagery in an image store.Each video clip of the video clip imagery is then image processed todetermine a view and a quality of each video clip and a rule isretrieved from a rules base corresponding to the selected diagnosticprocedure and target portion. In this regard, the rule specifies arequisite view and quality of the video clip imagery. Finally, theretrieved rule is applied to the video clip imagery as a filter toproduce a subset of video clip imagery satisfying the specifiedrequisite view and quality and the subset of video clip imagery isstored in the image store.

Additional aspects of the invention will be set forth in part in thedescription which follows, and in part will be obvious from thedescription, or may be learned by practice of the invention. The aspectsof the invention will be realized and attained by means of the elementsand combinations particularly pointed out in the appended claims. It isto be understood that both the foregoing general description and thefollowing detailed description are exemplary and explanatory only andare not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute partof this specification, illustrate embodiments of the invention andtogether with the description, serve to explain the principles of theinvention. The embodiments illustrated herein are presently preferred,it being understood, however, that the invention is not limited to theprecise arrangements and instrumentalities shown, wherein:

FIG. 1 is a pictorial illustration of a process for clip selection formedical imaging;

FIG. 2 is a schematic illustration of a data processing systemconfigured for clip selection for medical imaging; and,

FIG. 3 is a flow chart illustrating a process for clip selection formedical imaging.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the invention provide for video clip selection formedical device imaging and diagnostics. In accordance with an embodimentof the invention, a set of contemporaneously acquired video clips of amammalian organ are selected for processing and each video clip in theset is submitted to a neural network trained to classify each video clipaccording to a particular view of the organ and a modality utilized toacquire the video clip. The confidence produced by the neural networkserves as input to a function determinate of a quality of the videoclip. An intended use of the acquired video clips is then specified, forexample, to compute a measurement of the organ in furtherance of thecomputation of a measurement in respect to a specified diagnosticprocedure, and a rule from a rules base retrieved indicating a specificview, modality and quality requirement for the intended use. Optionally,the rule indicates a presentation arrangement of video clips in aviewer. Based upon the indication by the rule of the specific view,modality and quality requirement for the intended use, the acquiredvideo clips are filtered to produce a subset of video clips of thespecific view, modality and quality. Finally, the subset of video clipsis provided as input to a diagnostic viewer presenting the subset ofvideo clips for viewing by a health care professional. Optionally, theviewer arranges the presentation of the subset of video clips inaccordance with the rule. In particular, the arrangement of thepresentation of the subset of the video clips may include a re-orderingof the subset of the video clips so that the most relevant ones of thevideo clips are first presented to the health care professional.

In further illustration, FIG. 1 is a pictorial illustration of a processfor clip selection for medical imaging. As shown in FIG. 1, a medicalimaging device 100 acquires imagery in an image set 130 of a targetorgan in a mammalian body. Each image in the image set 130 reflects aspecific view of the target organ and has a particular quality. Chipselector logic 150 loads each of the images in the image set 130 anddetermines both a view reflected by the image and also a determinedquality 160. Thereafter, an intended procedure 110 is specified to themedical imaging device 100 and a specific rule 140 as to the requisitequality and view of imagery is selected from a rule table 120 based uponthe intended procedure 110 and optionally, a specified measurement to becomputed in furtherance of the intended procedure 110. The selected rule140 is provided to the chip selector logic logic 150.

The chip selector logic 150 applies the selected rule 140 to each imagein the image set 130 so as to create a filter 180 filtering or sorting(re-ordering) the image set 130 into an image subset 190 of only thoseimages having an assigned view and quality 160 sufficient to support thespecified procedure 110 and optionally, in an order with the mostdesirable view and quality positioned at a top of the ordering.Thereafter, to the extent that the chip selector logic 150 determinesthat one or more images are present in the image subset 190, the imagesubset 190 is stored in data store 175 for use in a medical diagnosis ofthe specified procedure 110. Otherwise, the chip selector logic 150 upondetecting an empty set 185 for the image subset 190 directs a prompt 195in the medical imaging device 100 indicating a need to re-acquire newimagery satisfying of either or both of requisite view or a requisitequality for the specified procedure 110.

The process described in connection with FIG. 1 may be implemented in adata processing system. In further illustration, FIG. 2 schematicallyshows a data processing system configured for clip selection for medicalimaging. The system includes a host computing system 200 that includesmemory 220, at least one processor 210 and a display 230. The hostcomputing system 200 also is coupled to a medical imaging device 250adapted to acquire medical imagery of target organs, and an image store240 into which the acquired medical imagery is stored. An operatingsystem 260 executes in the memory 220 of the host computing system 200.The operating system 260 supports the execution of program code of aclip selection module 300.

The program code of the clip selection module 300 is enabled uponexecution by the processor 210 in the memory 220 to receive in aninterface to the medical imaging device 250, an indication of aprocedure in respect to a target organ, along with a set of images inimage store 240 acquired by the medical imaging device 250 in respect tothe indicated procedure. The program code further is enabled duringexecution to analyze and assign to each image in the image set both aview and a quality of each image. In this regard, the program code ofthe clip selection module 300 may provide each image in the image set toa neural network 280 trained to produce a probabilistic indication of aquality and view for a provided image. Alternatively, the program codeof the clip selection module 300 may provide each image to a contentbased image retrieval system 270 able to compare the imagery of eachimage to a known set of imagery in order to classify each image inrespect to a particular view and a particular quality based upon imageryof a known view and a known quality.

Optionally, the content based image retrieval system 270 may indicate aquality based upon an appearance in an image of a landmark portion ofthe mammalian body expected to be shown in respect to the particularview of the image. Absence of the landmark indicates poor quality. Varydegrees of presence of the landmark indicates vary degrees of quality.For instance, a clear presence of a landmark in an image when expectedindicates good quality. Conversely, partial presence of the landmarkindicates mediocre quality.

As another option, an echo distance can be computed to each image interms of a disparity between a pose of an image acquisition deviceresulting in the image, and an optimum pose. More specifically, a set oftraining images each annotated with a known pose utilized to acquire acorresponding one of the training images, and optionally a deviationfrom an a prior known optimal pose to acquire a highest quality form ofthe training image, are correlated so that a subsequent image, whencompared to the training images, can result in identification of alikely pose variation referred to as an echo distance. The foregoing maybe achieved through content-based image retrieval or through a neuralnetwork trained with the training images to indicate the echo distance.A quality is then assigned to the subsequent image based upon acorrelated echo distance such that a threshold echo distance indicatespoorer quality than a smaller echo distance for the subsequent image.

As another option, the neural network 280 may indicate a recognized viewin a submitted video clip at a specified level of confidence.

Once the program code of the clip selection module 300 has established acomputed view and quality for each image in the image set, the programcode is further enabled to select a particular rule from a rules-basekeyed upon the indicated procedure and to apply the rule to each imagein the image set. In this regard, the determined view and quality ofeach image in the image set is provided as input to the particular rulein order to determine of the view and quality exceeds that required bythe particular rule. If so, the image is added to a subset of images inthe image store 240. Otherwise, the image is discarded. Once each imagein the image set has been processed by the particular rule, the programcode of the clip selection module 300 determines if any images persistin the subset in the image store 240. If not, the clip selection module300 directs the medical imaging device 250 to generate an alert in theinterface indicating a necessity to acquire additional imagery.

In even yet further illustration of the operation of the clip selectionmodule 300, FIG. 3 is a flow chart illustrating a process for clipselection for medical imaging. The processing begins in block 310 inwhich a target procedure and target organ is specified in an interfaceto the medical imaging device. In block 320, a rule is located for thespecified target procedure and target organ. Thereafter, in block 330, afirst image in an image set is retrieved from the data store and anassigned quality and view loaded into memory. Optionally, the retrievaloccurs in real-time during the acquisition of the image set by themedical imaging device. In block 340, the located rule is applied to theassigned quality and view in order to determine in decision block 350.In decision block 350, if the first image is of sufficient quality andview for the specified target procedure and target organ, the firstimage is added to a subset in block 360. Otherwise, the processcontinues in decision block 370.

In decision block 370, if additional images remain to be processed, inblock 380, a next image in the image set is selected for processing andthe process repeats through block 340 with the application of thelocated rule. Otherwise, in decision block 390 it is then determined ifany images exist in the subset. If so, in block 400 the subset isreturned for utilization in a diagnostic analysis of the targetprocedure. But otherwise, in block 410 a prompt in an interface to themedical imaging device is presented indicating a need to acquireadditional imagery of the requisite quality, the requisite view, orboth.

The present invention may be embodied within a system, a method, acomputer program product or any combination thereof. The computerprogram product may include a computer readable storage medium or mediahaving computer readable program instructions thereon for causing aprocessor to carry out aspects of the present invention. The computerreadable storage medium can be a tangible device that can retain andstore instructions for use by an instruction execution device. Thecomputer readable storage medium may be, for example, but is not limitedto, an electronic storage device, a magnetic storage device, an opticalstorage device, an electromagnetic storage device, a semiconductorstorage device, or any suitable combination of the foregoing.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network. The computer readable program instructions mayexecute entirely on the user's computer, partly on the user's computer,as a stand-alone software package, partly on the user's computer andpartly on a remote computer or entirely on the remote computer orserver. Aspects of the present invention are described herein withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems), and computer program products according toembodiments of the invention. It will be understood that each block ofthe flowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein includes anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which includes one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Finally, the terminology used herein is for the purpose of describingparticular embodiments only and is not intended to be limiting of theinvention. As used herein, the singular forms “a”, “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“includes” and/or “including,” when used in this specification, specifythe presence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

Having thus described the invention of the present application in detailand by reference to embodiments thereof, it will be apparent thatmodifications and variations are possible without departing from thescope of the invention defined in the appended claims as follows:

We claim:
 1. A method for clip selection for medical imaging comprising:receiving through an interface to a medical imaging device, a selectionof a diagnostic procedure and a target portion of a mammalian body;acquiring a multiplicity of video clip imagery of the target portionutilizing the medical imaging device; storing the video clip imagery inan image store; image processing each video clip of the video clipimagery to determine a view and a quality of each video clip; retrievinga rule from a rules base corresponding to the selected diagnosticprocedure and target portion, the rule specifying a requisite view andquality of the video clip imagery and also a presentation arrangement ofthe video clip imagery in the interface; applying the retrieved rule tothe video clip imagery as a filter to produce a subset of video clipimagery satisfying the specified requisite view and quality; and,storing the subset of video clip imagery in the image store along withthe specified presentation arrangement.
 2. The method of claim 1,further comprising: on condition that a video clip satisfying thespecified requisite view and quality in the video clip imagery isdetermined upon the application of the retrieved rule not to exist inthe video clip imagery, generating an alert through the interface of themedical imaging device.
 3. The method of claim 1, wherein the imageprocessing of each video clip comprises submitting each video clip to aneural network trained to generate output indicating a recognized viewin a submitted video clip at a specified level of confidence.
 4. Themethod of claim 1, wherein the image processing of each video clipcomprises submitting each video clip to a content-based image retrievalsystem adapted to compare a submitted video clip to a data store ofknown images of particular views so as to indicate a recognized view inthe submitted video clip.
 5. The method of claim 3, wherein the imageprocessing of each video clip further comprises computationallycomputing a generalized degree of quality of a submitted image basedupon the specified level of confidence produced in the output of theneural network.
 6. The method of claim 1, wherein the rule additionallyspecifies a requisite presence of a landmark feature in the view, andwherein the image processing of each video clip comprises submittingeach video clip to a neural network trained to generate outputindicating a recognized landmark feature in a submitted video clip at aspecified level of confidence, such that during application of theretrieved rule, an absence of the landmark feature correlates to poorquality of the video clip, but a presence of the landmark featurecorrelates to good quality of the video clip.
 7. The method of claim 1,wherein the storing occurs during real-time acquisition of themultiplicity of video clip imagery of the target portion utilizing themedical imaging device.
 8. A medical imaging data processing systemconfigured for clip selection, the system comprising: a host computingsystem comprising one or more computers, each including memory and atleast one processor; a diagnostic imaging computer program executing inthe memory of the host computing system, the program providing controlinstructions to a communicatively coupled medical imaging device, theprogram additionally providing an interface to the medical imagingdevice, the program yet further comprising computer program instructionsenabled during execution to perform: receiving through the interface aselection of a diagnostic procedure and a target portion of a mammalianbody; acquiring a multiplicity of video clip imagery of the targetportion utilizing the medical imaging device; storing the video clipimagery in an image store; image processing each video clip of the videoclip imagery to determine a view and a quality of each video clip;retrieving a rule from a rules base corresponding to the selecteddiagnostic procedure and target portion, the rule specifying a requisiteview and quality of the video clip imagery and also a presentationarrangement of the video clip imagery in the interface; applying theretrieved rule to the video clip imagery as a filter to produce a subsetof video clip imagery satisfying the specified requisite view andquality; and, storing the subset of video clip imagery in the imagestore along with the specified presentation arrangement.
 9. The systemof claim 8, wherein the program instructions are further enabled toperform: on condition that a video clip satisfying the specifiedrequisite view and quality in the video clip imagery is determined uponthe application of the retrieved rule not to exist in the video clipimagery, generating an alert through the interface of the medicalimaging device.
 10. The system of claim 8, wherein the image processingof each video clip comprises submitting each video clip to a neuralnetwork trained to generate output indicating a recognized view in asubmitted video clip at a specified level of confidence.
 11. The systemof claim 8, wherein the image processing of each video clip comprisessubmitting each video clip to a content-based image retrieval systemadapted to compare a submitted video clip to a data store of knownimages of particular views so as to indicate a recognized view in thesubmitted video clip.
 12. The system of claim 10, wherein the imageprocessing of each video clip further comprises computationallycomputing a generalized degree of quality of a submitted image basedupon the specified level of confidence produced in the output of theneural network.
 13. The system of claim 8, wherein the rule additionallyspecifies a requisite presence of a landmark feature in the view, andwherein the image processing of each video clip comprises submittingeach video clip to a neural network trained to generate outputindicating a recognized landmark feature in a submitted video clip at aspecified level of confidence, such that during application of theretrieved rule, an absence of the landmark feature correlates to poorquality of the video clip, but a presence of the landmark featurecorrelates to good quality of the video clip.
 14. A computer programproduct for clip selection for medical imaging, the computer programproduct including a non-transitory computer readable storage mediumhaving program instructions embodied therewith, the program instructionsexecutable by a device to cause the device to perform a methodincluding: receiving through an interface to a medical imaging device, aselection of a diagnostic procedure and a target portion of a mammalianbody; acquiring a multiplicity of video clip imagery of the targetportion utilizing the medical imaging device; storing the video clipimagery in an image store; image processing each video clip of the videoclip imagery to determine a view and a quality of each video clip;retrieving a rule from a rules base corresponding to the selecteddiagnostic procedure and target portion, the rule specifying a requisiteview and quality of the video clip imagery and also a presentationarrangement of the video clip imagery in the interface; applying theretrieved rule to the video clip imagery as a filter to produce a subsetof video clip imagery satisfying the specified requisite view andquality; and, storing the subset of video clip imagery in the imagestore along with the specified presentation arrangement.
 15. Thecomputer program product of claim 14, wherein the method performed bythe device further comprises: on condition that a video clip satisfyingthe specified requisite view and quality in the video clip imagery isdetermined upon the application of the retrieved rule not to exist inthe video clip imagery, generating an alert through the interface of themedical imaging device.
 16. The computer program product of claim 14,wherein the image processing of each video clip comprises submittingeach video clip to a neural network trained to generate outputindicating a recognized view in a submitted video clip at a specifiedlevel of confidence.
 17. The computer program product of claim 16,wherein the image processing of each video clip further comprisescomputationally computing a generalized degree of quality of a submittedimage based upon the specified level of confidence produced in theoutput of the neural network.
 18. The computer program product of claim14, wherein the image processing of each video clip comprises submittingeach video clip to a content based image retrieval system adapted tocompare a submitted video clip to a data store of known images ofparticular views so as to indicate a recognized view in the submittedvideo clip.
 19. The computer program product of claim 14, wherein therule additionally specifies a requisite presence of a landmark featurein the view, and wherein the image processing of each video clipcomprises submitting each video clip to a neural network trained togenerate output indicating a recognized landmark feature in a submittedvideo clip at a specified level of confidence, such that duringapplication of the retrieved rule, an absence of the landmark featurecorrelates to poor quality of the video clip, but a presence of thelandmark feature correlates to good quality of the video clip.
 20. Thecomputer program product of claim 14, wherein the storing occurs duringreal-time acquisition of the multiplicity of video clip imagery of thetarget portion utilizing the medical imaging device.